let's try something

app.py

@@ -3,14 +3,14 @@ import pandas as pd
 from run import run, GUIDE_LEN, NUCLEOTIDE_TOKENS
 
 
-def run_with_input(reset=False):
-    if reset:
-        st.write("")
-        return 0
-    returned_x = run(st.session_state["userInput"])
-    csv_x = returned_x.to_csv()
-    st.write("model prediction: ", returned_x)
-    return csv_x
+# def run_with_input(reset=False):
+#     if reset:
+#         st.write("")
+#         return 0
+#     returned_x = run(st.session_state["userInput"])
+#     csv_x = returned_x.to_csv()
+#     st.write("model prediction: ", returned_x)
+#     return csv_x
 
 
 # title and instructions
@@ -19,13 +19,14 @@ st.session_state['userInput'] = ''
 st.session_state['userInput'] = st.text_input('Enter target transcript (or substring):')
 
 
-csv_data = pd.DataFrame.from_dict({'Target Site': [''], 'LFC': [0.0]}).to_csv()
+predictions = pd.DataFrame.from_dict({'Target Site': [''], 'Normalized LFC': [0.0]})
 if len(st.session_state['userInput']) < GUIDE_LEN:
     st.write('Transcript length must be >= 23 bases. It is {:d} chars'.format(len(st.session_state['userInput'])))
-    run_with_input(reset=True)
+    st.write("")
 elif all([True if nt.upper() in NUCLEOTIDE_TOKENS.keys() else False for nt in st.session_state['userInput']]):
-    st.write('This is your sequence', st.session_state["userInput"])
-    csv_data = run_with_input()
+    st.write('This is your sequence', st.session_state['userInput'])
+    predictions = run(st.session_state['userInput'])
+    st.write('Model predictions: ', predictions)
 else:
     st.write('only ACTG is allowed')
-st.download_button(label='Download as CVS File', data=csv_data)
+st.download_button(label='Download as CVS File', data=predictions.to_csv())